论文标题
具有五个多目标现实世界工程问题的多目标学习者基于绩效的行为算法
Multi-objective learner performance-based behavior algorithm with five multi-objective real-world engineering problems
论文作者
论文摘要
在这项工作中，提出了一种新的多目标优化算法，称为多目标学习者性能行为算法。拟议的算法基于将学生从高中转移到大学的过程。提出的技术生产一组非主导的解决方案。为了判断拟议的多目标算法的能力和功效，它可以针对一组基准和五个现实世界的工程优化问题进行评估。此外，为了定量评估所提出的技术，应用了几种最广泛使用的指标。此外，结果可以从统计上确认。然后将提出的工作与三种多物镜算法进行比较，即Mowca，NSGA-II和MODA。与所提出的技术类似，文献中的其他算法与基准相反，以及本文中使用的现实世界工程问题。使用描述性，表格和图形演示的算法将算法相互比较。结果证明了拟议工作提供一组非主导解决方案的能力，并且在大多数情况下，该算法的表现优于其他参与算法。
In this work, a new multiobjective optimization algorithm called multiobjective learner performance-based behavior algorithm is proposed. The proposed algorithm is based on the process of transferring students from high school to college. The proposed technique produces a set of non-dominated solutions. To judge the ability and efficacy of the proposed multiobjective algorithm, it is evaluated against a group of benchmarks and five real-world engineering optimization problems. Additionally, to evaluate the proposed technique quantitatively, several most widely used metrics are applied. Moreover, the results are confirmed statistically. The proposed work is then compared with three multiobjective algorithms, which are MOWCA, NSGA-II, and MODA. Similar to the proposed technique, the other algorithms in the literature were run against the benchmarks, and the real-world engineering problems utilized in the paper. The algorithms are compared with each other employing descriptive, tabular, and graphical demonstrations. The results proved the ability of the proposed work in providing a set of non-dominated solutions, and that the algorithm outperformed the other participated algorithms in most of the cases.
